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Photometric Stereo for Specular Surface Shape Based on Neural Network
Yuji IWAHORI Hidekazu TANAKA Robert J. WOODHAM Naohiro ISHII
IEICE TRANSACTIONS on Information and Systems
Publication Date: 1994/04/25
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Neurocomputing)
Category: Image Processing
neural network, computer vision, shape from shading, photometric stereo, Phong reflectance function,
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This paper proposes a new method to determine the shape of a surface by learning the mapping between three image irradiances observed under illumination from three lighting directions and the corresponding surface gradient. The method uses Phong reflectance function to describe specular reflectance. Lambertian reflectance is included as a special case. A neural network is constructed to estimate the values of reflectance parameters and the object surface gradient distribution under the assumption that the values of reflectance parameters are not known in advance. The method reconstructs the surface gradient distribution after determining the values of reflectance parameters of a test object using two step neural network which consists of one to extract two gradient parameters from three image irradiances and its inverse one. The effectiveness of this proposed neural network is confirmed by computer simulations and by experiment with a real object.